Next Generation Sequencing of miRNAs – Strategies, Resources and Methods

Motameny, Susanne; Wolters, Stefanie; Nürnberg, Peter; Schumacher, Björn

doi:10.3390/genes1010070

Cited by 119 publications

(85 citation statements)

References 38 publications

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“…While mapping to known microRNA precursor databases can be a faster and more direct method to quantify microRNA expression, mapping smRNA reads to the entire genome is emerging as a consensus standard procedure (Motameny et al 2010, Farazi et al 2012, Stokowy et al 2014. Genome mapping allows identification of novel smRNAs, and can effectively identify transcripts of RNA classes such as rRNA, tRNA, and mRNA.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of microRNA alignment techniques

Ziemann

Kaspi²,

El‐Osta³

2016

RNA

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Genomic alignment of small RNA (smRNA) sequences such as microRNAs poses considerable challenges due to their short length (∼21 nucleotides [nt]) as well as the large size and complexity of plant and animal genomes. While several tools have been developed for high-throughput mapping of longer mRNA-seq reads (>30 nt), there are few that are specifically designed for mapping of smRNA reads including microRNAs. The accuracy of these mappers has not been systematically determined in the case of smRNA-seq. In addition, it is unknown whether these aligners accurately map smRNA reads containing sequence errors and polymorphisms. By using simulated read sets, we determine the alignment sensitivity and accuracy of 16 short-read mappers and quantify their robustness to mismatches, indels, and nontemplated nucleotide additions. These were explored in the context of a plant genome (Oryza sativa, ∼500 Mbp) and a mammalian genome (Homo sapiens, ∼3.1 Gbp). Analysis of simulated and real smRNA-seq data demonstrates that mapper selection impacts differential expression results and interpretation. These results will inform on best practice for smRNA mapping and enable more accurate smRNA detection and quantification of expression and RNA editing.

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Section: Introductionmentioning

confidence: 99%

Evaluation of microRNA alignment techniques

Ziemann

Kaspi²,

El‐Osta³

2016

RNA

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“…Deep sequencing, or next generation sequencing as it is also called, is a novel approach to discover new miRNAs as well as characterizing expression levels of annotated miRNAs [239]. One advantage of using deep sequencing opposed to microarrays is the ability to get absolute quantitative measurements instead of relative signal intensity [240].…”

mentioning

confidence: 99%

Investigation of nonspecific cross-reacting antigen 2 as a prognostic biomarker in bone marrow plasma from colorectal cancer patients

et al. 2011

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“…Experimental miRNA investigation are frequently supplemented by bioinformatic techniques, are used to develop raw sequencing data, discover mature sequences, miRNA genes, targets and precursors to determine isoforms, and organize small RNAs into identified miRNA families [59,60]. These computational and experimental techniques not only permit for economical, qualitative and quantitative small RNAs analysis, they also produce more precise results in a limited time period [61].…”

Section: Rna Sequencingmentioning

confidence: 99%

High Throughput Sequencing Advances and Future Challenges

Pervaiz¹,

Lotfi²,

Haider³

et al. 2017

J Plant Biochem Physiol

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High throughput sequencing (HTS) technologies were developed into indispensable for genomic investigation and recent hottest topic for research in the field of genomics, which can generate over 100 times more data in comparison with the most complicated capillary sequencers. Recent advances and developments in HTS using next generation sequencing techniques have become essential in the studies of digital gene expression profiling, in epigenomics, genomics, and transcriptomics. These methodologies are dexterous of sequencing multiple DNA molecules in corresponding; facilitate hundreds of millions of DNA molecules to be sequenced within a short period of time. Though, the expenses and time period have been significantly reduced; the inaccurate profiles and boundaries of the new policy differ considerably from those of earlier reported sequencing techniques. The technical developments and decreasing cost of NGS (Next Generation Sequencing) technology have made RNA sequencing (RNA-seq) as a worldwide popular technique for gene expression projects. Various approaches have been done for the standardization of RNA sequencing data, which have been materialized in the reports, contradictory, both in the type of bias modification and in the statistical approach. On the other hand, as data persistently build up, there has been no apparent consensus on the proper normalization techniques to be used or the impact of chosen methods on the downstream analysis. In the present article, we mentioned the key features of HT-NGS like, Key HTS platforms and different sequencing applications, ethical limitation and future prospective.

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Next Generation Sequencing of miRNAs – Strategies, Resources and Methods

Cited by 119 publications

References 38 publications

Evaluation of microRNA alignment techniques

Evaluation of microRNA alignment techniques

Investigation of nonspecific cross-reacting antigen 2 as a prognostic biomarker in bone marrow plasma from colorectal cancer patients

High Throughput Sequencing Advances and Future Challenges

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